Summary: Chemical mapping experiments allow for nucleotide resolution assessment of RNA structure. We demonstrate that different strategies of integrating probing data with thermodynamics-based RNA secondary structure prediction algorithms can be implemented by means of soft constraints. This amounts to incorporating suitable pseudo-energies into the standard energy model for RNA secondary stru...

Motivation Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidir...

Background: Multiple sclerosis (MS) is the most common autoimmune disease of the central nervous system (CNS). The main cause of the MS is yet to be revealed, but the most probable theory is based on the molecular mimicry that concludes some infections in the activation of T cells against brain auto-antigens that initiate the disease cascade.Objectives: The Purpose of this research is the...

We developed a methodology to predict myotoxicity and neurotoxicity of proteins of the family of Phospholipases A2 (PLA2) from sequence data. Combining two bioinformatics tools, MEME and HMMER, it was possible to detect conserved motifs and represent them as Hidden Markov Models (HMMs). In ten-fold cross validation testing we have determined the efficacy of each motif on prediction of PLA2 func...

MOTIVATION We introduce a development platform especially tailored to Bioinformatics research and software development. BIAS (Bioinformatics Integrated Application Software) provides the tools necessary for carrying out integrative Bioinformatics research requiring multiple datasets and analysis tools. It follows an object-relational strategy for providing persistent objects, allows third-party...

The immensely popular fields of cancer research and bioinformatics overlap in many different areas, e.g. large data repositories that allow for users to analyze data from many experiments (data handling, databases), pattern mining, microarray data analysis, and interpretation of proteomics data. There are many newly available resources in these areas that may be unfamiliar to most cancer resear...

Bioinformatics plays an essential role in today's plant science. As the amount of data grows exponentially, there is a parallel growth in the demand for tools and methods in data management, visualization, integration, analysis, modeling, and prediction. At the same time, many researchers in biology are unfamiliar with available bioinformatics methods, tools, and databases, which could lead to ...

Despite the central place held by bioinformatics in modern life sciences and related areas, it has only recently been integrated to a limited extent into high-school teaching and learning programs. Here we describe the assessment of a learning environment entitled 'Bioinformatics in the Service of Biotechnology'. Students' learning outcomes and attitudes toward the bioinformatics learning envir...

RNA secondary structure prediction is one of the major topics in bioinformatics. A prediction method based on a parsing algorithm for formal grammars is a promising approach. Also, it is expected that comparative sequence analysis achieves higher accuracy than the one using a single sequence since the former approach can use evolutionary information that homologous RNAs are likely to conserve a...